- Volume 22 Issue 2
DOI QR Code
A Two Sample Test for Functional Data
- Lee, Jong Soo (Department of Mathematical Sciences, University of Massachusetts Lowell) ;
- Cox, Dennis D. (Department of Statistics, Rice University) ;
- Follen, Michele (Department of Obstetrics and Gynecology, Brookdale University Hospital and Medical Center)
- Received : 2014.11.24
- Accepted : 2015.01.31
- Published : 2015.03.31
We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.
Supported by : NIH-NCI
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